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Improved individual and population-level HbA1c estimation using CGM data and patient characteristics

Machine learning and linear regression models using CGM and participant data reduced HbA1c estimation error by up to 26% compared to the GMI formula, and exhibit superior performance in estimating the median of HbA1c at the cohort level, potentially of value for remote clinical trials interrupted by...

Deskribapen osoa

Gorde:
Xehetasun bibliografikoak
Argitaratua izan da:J Diabetes Complications
Egile Nagusiak: Grossman, Joshua, Ward, Andrew, Crandell, Jamie L., Prahalad, Priya, Maahs, David M., Scheinker, David
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: Elsevier Inc. 2021
Gaiak:
Sarrera elektronikoa:https://ncbi.nlm.nih.gov/pmc/articles/PMC8316291/
https://ncbi.nlm.nih.gov/pubmed/34127370
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jdiacomp.2021.107950
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